LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Statistical and expert-based landslide susceptibility modeling on a national scale applied to North Macedonia

Photo by janesky from unsplash

Abstract This article presents a Geographic Information System (GIS) assessment of Landslide Susceptibility Zonation (LSZ) in North Macedonia. Because of the weak landslide inventory, statistical method (frequency ratio) is combined… Click to show full abstract

Abstract This article presents a Geographic Information System (GIS) assessment of Landslide Susceptibility Zonation (LSZ) in North Macedonia. Because of the weak landslide inventory, statistical method (frequency ratio) is combined with Analytical Hierarchy Process (AHP). In this study, lithology, slope, plan curvature, precipitations, land cover, distance from streams, and distance from roads were selected as precondition factors for landslide occurrence. There are two advantages of the approach used. The first is the possibility of comparing of the results and cross-validation between the statistical and expert based methods with an indication of the advantages and drawbacks of each of them. The second is the possibility of better weighting of precondition factors for landslide occurrence, which can be useful in cases of weak landslide inventory. The final result shows that in the case of weak landslide inventory, LSZmap created with the combination of both models provide better overall results than each model separately.

Keywords: landslide susceptibility; expert based; north macedonia; statistical expert

Journal Title: Open Geosciences
Year Published: 2019

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.